PROJECT TITLE :

Aerodynamic Shape Optimization via Global Extremum Seeking

ABSTRACT:

Optimization of aerodynamic shapes using computational fluid dynamics (CFD) approaches has been successfully demonstrated over a number of years; but, the everyday optimization approaches used utilize gradient algorithms that guarantee only the local optimality of the solution. Whereas numerous international optimization techniques exist, they are typically too time consuming in apply. In this temporary, a modified international optimization algorithm (DIRECT-L) is introduced and is used in the context of sampled-data global extremum seeking. The theoretical framework and conditions below that the convergence to the steady state of the CFD solver will be interpreted as plant dynamics are stated. This method alleviates the computational burden by reducing sampling and requiring only partial convergence of the CFD solver for every iteration of the optimization design process. The approach is demonstrated on a simple example involving drag minimization on a two-D aerofoil.